Digital Posters AAIN 2026 Conference
P12: Beyond Upskilling: Building AI Capability for Educators
Inez Chai and Lorna Clark, Navitas Learning and Teaching Services
The rapid emergence of generative artificial intelligence (GenAI) in higher education has intensified the need for coherent, research‑informed approaches to teacher capability development. This paper presents the ideal teacher capability development project currently undertaken by Navitas UPA, grounded explicitly in five interrelated capability dimensions identified across contemporary higher‑education GenAI scholarship: (1) technical and GenAI literacy, (2) pedagogical integration, (3) assessment redesign, (4) ethical, inclusive and responsible practice, and (5) sustained institutional and community support.
The project recognises that technical familiarity with GenAI tools alone is insufficient. Teachers require foundational understanding of how GenAI systems operate, their limitations, and how to critically evaluate outputs in order to use them confidently and responsibly. Equally, pedagogical capability is essential to ensure GenAI is embedded purposefully within teaching and learning activities, rather than positioned solely as a productivity tool. Assessment capability is foregrounded as a critical dimension, as traditional assessment practices are increasingly misaligned with GenAI enabled learning environments and require systematic redesign to preserve validity, transparency and academic integrity.
Ethical and inclusive capability underpins all other dimensions, ensuring attention to bias, privacy, transparency, equity of access and the protection of students’ learning and agency. Finally, the project emphasises that sustainable capability development depends on institutional support structures, clear guidance, and practice networks that enable ongoing professional learning and shared sense‑making, rather than one‑off training interventions.
By explicitly targeting these five dimensions, the Navitas UPA initiative responds directly to documented gaps in higher‑education teacher preparation for GenAI and offers a transferable model for institutions seeking to move beyond ad‑hoc upskilling toward coherent, future‑oriented teacher capability development.
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